The curriculum for the Bioinformatics and Genomics Master’s Program has been developed specifically to prepare students for entry level bioinformatics positions in academic, government, and industry labs. Students will typically spend nine months on campus developing critical foundational skills followed by a nine month paid internship. Most students will complete their Master’s degree in 18 months.
|Intensive summer courses||Summer||12 Credits|
Students will begin the program in the summer term with three intensive, 4 credit, workshop-style courses that will provide them with the skills to generate and analyze next generation sequencing data. The advantage of teaching these courses during the summer is that these sequential and overlapping courses will be full-time and intensive resulting in better training for the students.
- Computational Methods in Genomic Analysis:
The primary goal for this course is to teach students think algorithmically. Students learn how to write scripts using Bash and Python to manage and analyze next generation sequencing (NGS) data.Textbooks: Think Python: How to Think Like a Computer Scientist. Allen B Downey. O’ Reilly. Second Edition. 2015. We provide this book to our students. It is also available as a free ebook here.
A Primer for Computational Biology. Shawn T. O’Neil. Oregon State University Press. We lend students this book from the Bioinformatics Library. It is also available as a free ebook here.
- Genomics Techniques:
In this course, students learn about experimental design and learn the molecular techniques to prepare their own NGS libraries. The course also aims to improve students’ scientific communication skills (both written and oral) with a focus on communicating biological science. Textbooks: Barker, Kathy. At the Bench: A Laboratory Navigator. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory, 2005. Print. We lend students this book from the Bioinformatics Library.
Watson, Baker, Bell, Gann, Levine, and Losick. Molecular Biology of the Gene. 7th ed. Cold Spring Harbor: Cold Spring Harbor Laboratory, 2014. Print. We lend students this book from the Bioinformatics Library.
- Topics in Genomic Analysis:
Students will be introduced to wide-ranging topics including phylogenetics, transcriptome assembly, and differential expression analysis, among others. Textbook: Pevsner, Jonathan. Bioinformatics and Functional Genomics. 2nd ed. Hoboken, NJ: Wiley-Liss, 2009. Print. We lend students this book from the Bioinformatics Library.
|Continuing coursework||Fall and Winter||18-26 Credits|
Students continue their coursework in the fall and winter, extending and building upon the knowledge and skills they acquired during the summer term.
- Advanced Biological Statistics – Fall:
This course aims to provide students with an understanding of the core concepts and approaches for the analysis of biological data, particularly large data sets. This is meant as a ﬁrst, foundational course for graduate students. It is advanced in that we will move through the material quickly with the goal of covering all major topics in univariate and multivariate data analysis, forming a foundation for subsequent learning.
- Genomics Lab – Fall:
In this course, students will write algorithms to analyze NGS data. In addition to expanding upon topics presented in the third summer class, students will also be exposed to new topics in genomics analysis. Students will analyze raw NGS data to answer specific biological questions, working in a team setting.
- Professional Communication in the Sciences – Fall
In this one credit course, students will practice professional scientific communication.
- Advanced Biological Statistics II – Winter:
This course builds on the foundational topics presented in the Fall course, again with a focus on large, biological data sets.
- Genomics Lab II – Winter:
Students continue to build on the projects they begin in the Fall term, as well as gain exposure to a number of special topics/projects throughout the term.
- Professional Communication in the Sciences II – Winter
Students will work to identify and prepare for internships through a variety of workshops.
- Advanced Biological Statistics – Fall:
- Optional graduate level elective course – Fall and/or Winter (some examples of classes taken by our students in previous years include):
- Bi 525 – Advanced Molecular Biology Research Lab
- Bi 527 – Molecular Genetics of Human Disease
- BI 533 – Bacterial-Host Interactions
- For students with more extensive computer science background or those looking to challenge themselves:
- CIS 551 – Database Processing
- CIS 571 – Intro to Artificial Intelligence
- CIS 610 – Big Data and Data Science
- For more information visit:
The remaining 30 credits (10 credits per term) for the Master’s degree will be obtained through hands on training in an industrial, medical, or academic setting. Internships are not guaranteed, and students need to remain in good standing with the program in order to interact with program partners (satisfactory completion of all coursework and professional development activities). Students may interview during the winter term with program partners to secure an internship position. The program facilitates these opportunities. If students are interested in alternative opportunities, this may be discussed with the program director to determine if the internship satisfies program requirements. More information about the internship can be found here.